Evidence map›Paper›PMID 36849917›Full record

ArticleBMC bioinformatics2023

Reconstructing B cell lineage trees with minimum spanning tree and genotype abundances.

Nika Abdollahi, Lucile Jeusset, Anne de Septenville, Frederic Davi, Juliana Silva Bernardes

Abstract read
In one paragraph

Article in BMC bioinformatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. B cell tolerance and autoimmunity: Lessons from repertoires.The Journal of experimental medicine · 2024
    Review
  6. Article
  7. Review
  8. TRIBAL: Tree Inference of B cell Clonal Lineages.bioRxiv : the preprint server for biology · 2023
    Article
  9. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Nika AbdollahiUMR 7238, Laboratoire de Biologie Computationnelle et Quantitative, Sorbonne University, Paris, France.
Lucile JeussetUMR 7238, Laboratoire de Biologie Computationnelle et Quantitative, Sorbonne University, Paris, France.
Anne de SeptenvilleAP-HP, Hôpital Pitié-Salpêtrière, Department of Biological Hematology, Sorbonne University, Paris, France.
Frederic DaviAP-HP, Hôpital Pitié-Salpêtrière, Department of Biological Hematology, Sorbonne University, Paris, France.
Juliana Silva BernardesUMR 7238, Laboratoire de Biologie Computationnelle et Quantitative, Sorbonne University, Paris, France. juliana.silva_bernardes@sorbonne-universite.fr.

Funding

SIRIC CURAMUS S20JRAP016 2020-2021
6 · The paper itself

Abstract

B cell receptor (BCR) genes exposed to an antigen undergo somatic hypermutations and Darwinian antigen selection, generating a large BCR-antibody diversity. This process, known as B cell affinity maturation, increases antibody affinity, forming a specific B cell lineage that includes the unmutated ancestor and mutated variants. In a B cell lineage, cells with a higher antigen affinity will undergo clonal expansion, while those with a lower affinity will not proliferate and probably be eliminated. Therefore, cellular (genotype) abundance provides a valuable perspective on the ongoing evolutionary process. Phylogenetic tree inference is often used to reconstruct B cell lineage trees and represents the evolutionary dynamic of BCR affinity maturation. However, such methods should process B-cell population data derived from experimental sampling that might contain different cellular abundances. There are a few phylogenetic methods for tracing the evolutionary events occurring in B cell lineages; best-performing solutions are time-demanding and restricted to analysing a reduced number of sequences, while time-efficient methods do not consider cellular abundances. We propose ClonalTree, a low-complexity and accurate approach to construct B-cell lineage trees that incorporates genotype abundances into minimum spanning tree (MST) algorithms. Using both simulated and experimental data, we demonstrate that ClonalTree outperforms MST-based algorithms and achieves a comparable performance to a method that explores tree-generating space exhaustively. Furthermore, ClonalTree has a lower running time, being more convenient for building B-cell lineage trees from high-throughput BCR sequencing data, mainly in biomedical applications, where a lower computational time is appreciable. It is hundreds to thousands of times faster than exhaustive approaches, enabling the analysis of a large set of sequences within minutes or seconds and without loss of accuracy. The source code is freely available at github.com/julibinho/ClonalTree.

Indexed as

B-LymphocytesReceptors, Antigen, B-CellCell LineageGenotypePhylogenyReceptors, Antigen, B-CellB cell receptor repertoireLineage Treephylogenetics

Identifiers

PMID36849917
PMCPMC9972711

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.